Nonparametric Function Estimation and Visualization with Applications to C2
Final rept. 1 Aug 1999-31 Dec 2002
GEORGE MASON UNIV FAIRFAX VA
Pagination or Media Count:
This project focused on the development of fast, accurate density estimation procedures. The methods raised basic research issues as to the implementation, computational complexity, visualization, and optimization of estimators in this class. In addition to being useful in a direct role, it is argued that density estimation plays a crucial role in clustering algorithms, discriminant methods and pattern recognition. All of these methods are used extensively in Situation and Informational Awareness and Understanding and in Monitoring and Discovery Processes. In addition, because of their intuitive appeal and ease in understanding, visually rendered density and function estimators provide a natural format for human-computer interactions with decision makers. This report describes results related implementation, computational complexity, visualization, optimization and application of recursive orthonormal density estimators.
- Statistics and Probability
- Computer Programming and Software